Analyzing Einstein Toolkit simulations can be a challenging task. Usually, the
process involves a series of technical obstacles like combining data from
different restarts or working with HDF5 files. In this talk, I will present
kuibit, a Python3.6+ library that takes care of all these low-level details (and
many other more) and that provides high-level, intuitive, representations of the
data. Kuibit comes with a wide range of features that include full support for
1-3D ASCII and HDF5 grid data, time and frequency series, gravitational waves,
and apparent horizons. With kuibit, users can inspect most of the content of a
simulation with just a few lines of code. Importantly, kuibit is designed to be
a code for the community: it is user-friendly and does not require any
proprietary software to run, it has documentation and examples, and it is openly
developed with emphasis on extensibility and maintainability. In the talk, I
will first give a general overview of the project, then I will discuss in more
details the various modules.